Atlas Physics studiesstrauss/DOE/Saleem_Physics_CERN_DOE10...02/01/2010 M. Saleem (University of...

02/01/2010 M. Saleem (University of Oklahoma) 1

Atlas Physics studies

(DOE Review) Feb. 01, 2010

M. Saleem (university of Oklahoma)


Outline

  Introduction   Top Cross-section study   Atlas Data arrival and Study   Performace Study

  Fake rates for Btagging   validation   Cosmic ray & MinBias study

02/01/2010 M. Saleem (University of Oklahoma) 3 M. Saleem, OU 3

Introduction   The focus of my talk is on the Physics/software activities and

involvement of the Oklahoma group based in CERN.   Including Myself (+ 2 GS), there are 3 people based in CERN

for this effort.

  Focus of our activities during the year 2009 was as follow:   Finished ttbar cross-section studies on MC – ATLAS INTERNAL

Note approved.   Started our activities to be ready on expected ATLAS data (spring

10) for the C.o.M 7 TeV.   Activity on Atlas Data in (Nov.- Dec) 2009.   Work on the Btagging performance – Mistag rate measurements   Btag Perfromance Mangement Board involvement. (Saleem)   MC validation work (Dilip)   MiniBias Study (Razzak)   Future Plans.


Why top pair cross-section:   σ(tŧ) is an inclusive quantity that allows:   Test the SM at the LHC energies (LHC is a top factory),   Compare the experimental measurement with the QCD NLO

predictions,   Extract the top quark mass and compare with theory

measurements.   Probe new Physics,

  like anomalous ttbar production rate,   compare cross-section in different decay channels,

  Well understood ttbar selection can be used to study the top properties.

  Background for Higgs, SUSY and new phenomena searches..   Top Decay in the SM: BR(t->wb)~100%   Final state driven by the w decay modes.

02/01/2010 M. Saleem (University of Oklahoma) 5 5

Analysis strategy: At C.o.M = 10TeV

Selection: Lepton:e or µ (only one lepton:

Pt > 20 GeV ; |η|<2.5 MET > 20 GeV

At least 4 jets > 20 GeV 3 out of 4 jets> 40 GeV; |η|<2.5

: e + jets channel: 6.01±0.04% S/B (after preselection) = 1.6 µ + jets channel:7.23±0.04% S/B (after preselection) = 1.5

(at 50 pb-1)

1.  Number of signal events is fitted to a Likelihood distribution build out of 8 variables: chosen

•  so that there distribution data is expected to be accurately re -produced by MC, •  They have either minimal or no dependence on JES (biggest systematic error) •  And they are not highly corelated. These variables are optimized for best statistical error with 50 pb-1

µ + jets channel e + jets channel


Analysis Results and Approval: For µ + jets channel at 50 pb1

For e + jets channel at 50 pb1

Analysis is Approved as Atlas Internal Note


Plans on Data :   Now we are getting ready   For this analysis to be published as one of the early papers.   We expect to have enough data this year at 7 TeV C.o.M   Work already been started for tunning up our tools on 7 TeV MC samples.


Btagging: Mistag Rate Measurement   People involved: , A. Khanov(OSU)   Major sources that lead to tagging of the light jets:

  finite resolution of the reconstructed track/vertex parameters   Tracks/vertices from the long-lived particles that decay in jets

  We cannot measure the mis-tagging rate directly on data -- need 100 % pure light jet sample, which is not possible due to the presence of heavy flavor (b, c jets) in inclusive sample.

  Two different approaches to deal with this issue: : To a good approximation the resolution of the

track impact parameter significance or secondary vertex significance (DLS) is perfectly symmetric arround zero, and the contribution from long-lived particles can be effectively suppressed, the “negative” tagging rate should be close to the “positive” tagging rate. By looking at tracks with negative DCAS or vertices with negative DLS, we can estimate the mis-tag rate on a sample with heavy flavor admixture.


Btagging: Mistag Rate Measurement is a distribution of tag weights w for a given

flavor of jets, put in a histogram of N bins and normalized to 1.   Split the sample into a pair of samples with different heavy flavor composition.   Assume that distributions of tag weights for b-, c- jets are known (e.g; b from a

measurement in data and c from b+c/b evaluated on MC).   The light tag weight distribution is unknown, but assumed to be same in in both

samplesIf tag weight distributions consists of N bin , have 2N equations for the number of events in each bin for each of the 2 samples and N+3 unknowns (b-, c-fractions in each of the 2 samples and N bins of the light tag weight)

  If enough bins, can resolve this system and find the b-, c fraction and mistag rate at once by assuming that heavy flavor fraction is already known with infinite accuracy.


Btagging: Mistag Rate Measurement

 Measuement __ True


Road towards Real Data:   End of Nov. and early Dec. 2009. Atlas collected some data on 900 GeV

and 2.36 TeV (for short time).


Road towards Real Data:   End of Nov. and early Dec. 2009. Atlas collected some data on 900 GeV

and 2.36 TeV (for short time).   Data: 263805 , MC: 980994 events. (with cone4 Jet algorithm)   6595 jets in data (~2.4 %) ; 19620 jets in MC (~2.0%)

d0/σ(/PV) signed w.r.t jet axis d0(/PV) signed w.r.t jet axis

Ent

ries/

1.6µ

m

Ent

ries/

0.1

Lifetime signed IP Lifetime IP significance


SoftwarePerfomance Management Board   Saleem is memeber of the Performance Management Board (PMB),

representing the Combined Reconstruction for the Flavor tagging working group. (Since 2009 Summer).

  The PMB is responsible for ensuring that the cpu and memory usage of ATLAS jobs is compatible with the processing requirements and the production system constraints. This compatibility will be maintained throughout ATLAS detector commissioning, initial collisions, and design luminosity involving pile-up and cavern backgrounds. This responsibility includes:

  The development of, and the incorporation of existing, monitoring and diagnostic tools into the ATLAS software development and production environments (In conjunction with b-tagging specific algorithms, tools..).

Memory(MB) CPU(ms) Btag ON 185.972 745.408 Btag OFF 185.676 582.525 Delta 0.296 162.883 Fraction of Off

0.001594 0.279615 One special busy event

Btag was ON

Btag was Off


Validation effort   One of GS (Dilip) is involved in the top working group Software

release Validation work (Since 2009 September).   Physics Validation is part of the new ATLAS software Release Validation

scheme which was started in March 2007 with the aim of greatly improving the speed and thoroughness of ATLAS software validation. Results of Physics validation studies are presented in Physics Validation group meetings.

  This Dataset: valid1.105200.T1_McAtNlo_Jimmy.recon.AOD.panda_e380_s593_r916 Reference Dataset: valid1.105200.T1_McAtNlo_Jimmy.

recon.AOD.panda_e380_s593_r896_test

Electron Efficiency (Et)

Muon Efficiency (Et)


MiniBias Study   One of GS (Razzak) has recently started working on the MiniBias

study using the 900 GeV data (taken during Nov – Dec. 2009)

  This will be part of Ph.D. thesis

Detection Efficiency of the Atlas pixel Detector using sensor overlap region with cosmics ray data

MinBias studies in low pt regions Pt<500MeV. including efficiency measurements of silicon vs TRT. For tracks migrating from low Pt region to High Pt region due to the mis-reconstruction of tracks.


The End

M. Saleem (University of Oklahoma) 18 01/27/2010

Mistag Rate: Negative Tag Method  Use IP based (IP3D) and secondary vertex based (SV1).

 Signed DCA/DLS significance for light and b-jets & weights distribution

Tracks from light jets: almost symmetric, positive tail is due to long-lived particles

positive tail is due to Tracks from b-decays, used to identify b-jets.

Negative tail is for tracks from b-decay due to wrong IP Sign for tracks Close to jet axis

Tag weight

DLS

SV1 IP3D


Correction Factors (Kll)

We assign systematic uncertainty on the value of Kll due to material and V0’s by removing the jets with tracks which are known to originate due to above mentioned sources and then re-evaluating the correction factor.

Misreco Conversions Interactions Hyperons K-short Residual HF

Misreco

Interactions Conversions

Hyperons K-short Residual HF


Measured and True Mistag rate


Systematic Error for the Method I

For SV1 taggers with two different Operating points.

For IP3D taggers with two different Operating points.


Statistical and Systematic uncertainty (II)

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